P577: 20% BLAST CRITERIA FOR DIAGNOSING AML/MDS: IS IT TIME TO MOVE BEYOND?
Authors: V. Sheth, R. Walter, C. Shaw, E. Estey, M.-B. Percival
Journal: HemaSphere (2022)

Background: Classification of acute myeloid leukemia (AML) and myelodysplastic syndromes (MDS) is driven by an arbitrary blast percentage cut off (20%, using the 2016 WHO criteria), which subsequently affects treatment options (including enrollment in clinical trials) without taking genomic and biological characteristics into consideration. It has recently been posited that AML and MDS with excess blasts (EB) exist on a continuum based on biological features rather than blast percentages, and their outcomes post treatment are very similar. Aims: We therefore hypothesized that the IPSS-R (MDS prognostication using hematologic parameters and cytogenetic features) should predict outcomes for WHO-defined AML, and similarly, ELN2017 (AML prognostication using molecular and cytogenetic features) should predict outcomes for WHO-defined MDS-EB (5-19% blasts). Methods: We retrospectively analyzed 1034 adult patients from the UW/FHCRC registry database, who received treatment for AML or MDS-EB between the years 2005-2018. WHO-defined AML occurred in 777 patients (67%) and WHO-defined MDS-EB in 257 (23%). Median follow up was 5 years. Outcomes were relapse-free survival (RFS) and overall survival (OS). Results: Median age of patients in AML group was 63 years (range 18-91), and in MDS group was 60 years (range 22-85). The majority of the patients in AML cohort had intermediate (37%) or high-risk disease (37%) using ELN2017 classification; many were reclassified to very high risk by IPSS-R (54%). Most of the patients in MDS cohort were very high risk (54%) using IPSS-R; many were reclassified to ELN high risk (46%). For AML patients, classification using the IPSS-R was highly predictive of OS for AML in univariate (p=0.001) and multivariate analysis (reference low risk/intermediate risk) (p=0.001, HR-2.1, 95% confidence interval (CI) 1.1-2.9 for very high risk and p=0.2, HR-1.4, 95%CI 0.76- 1.9 for high risk in AML), as well as RFS in univariate (p=0.001) and multivariate analysis (reference low risk/intermediate risk) (p=0.001, HR-2.08, 95%CI 1.2-2.8 for very high risk and 0.2, HR-1.4, 95%, CI 0.2-1.8 for high risk in AML). Similarly, ELN 2017 was predictive of OS in MDS cohort in univariate (p=0.025), and multivariate analysis (reference ELN adverse (p=0.005, HR-0.1, 95%CI 0.02-0.5, ELN favorable risk), as well as RFS in univariate (p=0.043) and multivariate analysis (reference ELN adverse) (p=0.019, HR-0.25 for ELN favorable risk, 95%CI 0.04- 0.8). In the subgroup of AML patients who achieved CR/CRi, IPSS-R was predictive of RFS in univariate analysis (p=<0.001), and multivariate analysis (ref low/int) (p=0.001, HR=2.08 for very high risk). Similarly, in the subgroup of MDS patients who achieved CR/CRi, ELN 2017 was predictive of RFS (p=<0.001), but this effect was not sustained in multivariable analysis. Summary/Conclusion: Data from our cohort suggest that IPSS-R can be predictive of survival outcomes in WHO-defined AML patients and ELN 2017 can similarly be predictive in WHO-defined MDS patients. Therefore, we suggest that diagnostic criteria for AML and MDS should include more biological and genomic features rather than a blast percentage cut-off, using tools such as the recently presented IPSS-molecular for MDS. Clinical trials of new therapies should include all patients having 35% blasts (MDS-EB and AML). This study, however, carries a potential drawback of retrospective classification and lack of complete molecular data through comprehensive targeted next generation sequencing panel in patients treated at earlier time periods